Honcho Model Card
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Honcho Model Card
| Field | Value |
|---|---|
| Repository | plastic-labs/honcho |
| Category | Agent Memory Infrastructure |
| Stars / forks snapshot | 4200 / 488 |
| Language | Python |
| License | AGPL-3.0 |
| Raw capture | raw-github/plastic-labs_honcho.md |
| Updated by | hourly public metadata update, 2026-05-25 11:20 +0800 |
1. Role in Self Evolve
Honcho is memory infrastructure for stateful agents, modeling peers, sessions, messages, representations and background reasoning so agents can carry durable context across conversations and tools.
2. Working Principle
messages/events -> background reasoning -> peer/session representations -> context/search/chat endpoints -> agent injection
3. Evidence Path
web GitHub page observed 527 commits, AGPL-3.0 license, Python/TypeScript stack, 4.2k stars and 488 forks; README describes memory infrastructure for stateful agents, peer/session/message primitives, MCP/OpenCode/OpenClaw/Hermes integrations and self-hosted FastAPI deployment. Shell GitHub API access remained DNS-blocked and the local gh token was invalid in this run, so this card treats the current snapshot as web-observed rather than API-verified.
4. Teaching Use
Use this card to explain how Honcho fits the raw -> classification -> project card -> site/report pipeline. It is useful for comparing whether self-evolution is implemented as memory substrate, trace learning, context graph grounding, or benchmark/evaluation infrastructure.
5. Limits
当前未克隆源码，未运行 benchmark、skill install flows、memory experiments、MCP servers、agent evolution loops、security scanners 或 production deployments；star/fork/commit/release 快照来自公开 GitHub 页面文本或可见页面片段。